IDEAS home Printed from https://ideas.repec.org/p/ubc/pmicro/vadim_marmer-2010-22.html
   My bibliography  Save this paper

Supplement to "What Model for Entry in First-Price Auctions? A Nonparametric Approach"

Author

Listed:
  • Marmer, Vadim
  • Shneyerov, Art
  • Xu, Pai

Abstract

The paper contains supplemental material for Marmer, Shneyerov, and Xu (2010) "What Model for Entry in First-Price Auctions? A Nonparametric Approach."

Suggested Citation

  • Marmer, Vadim & Shneyerov, Art & Xu, Pai, 2010. "Supplement to "What Model for Entry in First-Price Auctions? A Nonparametric Approach"," Microeconomics.ca working papers vadim_marmer-2010-22, Vancouver School of Economics, revised 18 Feb 2011.
    • Handle: RePEc:ubc:pmicro:vadim_marmer-2010-22
    as

    Download full text from publisher

    File URL: http://microeconomics.ca/vadim_marmer/selectentry-suppl-02.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marmer, Vadim & Shneyerov, Artyom & Xu, Pai, 2013. "What model for entry in first-price auctions? A nonparametric approach," Journal of Econometrics, Elsevier, vol. 176(1), pages 46-58.
    2. Newey, Whitney K., 1994. "Kernel Estimation of Partial Means and a General Variance Estimator," Econometric Theory, Cambridge University Press, vol. 10(2), pages 1-21, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vivek Bhattacharya & James W. Roberts & Andrew Sweeting, 2014. "Regulating bidder participation in auctions," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 675-704, December.
    2. Florencia M. Gabrielli, 2013. "Detecting Collusion on Highway Procurement," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 59, pages 127-165, January-D.
    3. Marmer, Vadim & Shneyerov, Artyom & Xu, Pai, 2013. "What model for entry in first-price auctions? A nonparametric approach," Journal of Econometrics, Elsevier, vol. 176(1), pages 46-58.
    4. Jehiel, Philippe & Lamy, Laurent, 2014. "On discrimination in procurement auctions," CEPR Discussion Papers 9790, C.E.P.R. Discussion Papers.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2019. "Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator," Journal of Econometrics, Elsevier, vol. 211(2), pages 507-538.
    2. Jun Ma & Vadim Marmer & Artyom Shneyerov & Pai Xu, 2021. "Monotonicity-constrained nonparametric estimation and inference for first-price auctions," Econometric Reviews, Taylor & Francis Journals, vol. 40(10), pages 944-982, November.
    3. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Matthew Gentry & Tong Li & Jingfeng Lu, 2015. "Identification and estimation in first-price auctions with risk-averse bidders and selective entry," CeMMAP working papers CWP16/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    7. Jesus Gonzalo & Jose Olmo, 2014. "Conditional Stochastic Dominance Tests In Dynamic Settings," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 819-838, August.
    8. Rina Friedberg & Julie Tibshirani & Susan Athey & Stefan Wager, 2018. "Local Linear Forests," Papers 1807.11408, arXiv.org, revised Sep 2020.
    9. Shakeeb Khan & Arnaud Maurel & Yichong Zhang, 2023. "Informational Content of Factor Structures in Simultaneous Binary Response Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 385-410, Emerald Group Publishing Limited.
    10. Nir Billfeld & Moshe Kim, 2024. "Context-dependent Causality (the Non-Nonotonic Case)," Papers 2404.05021, arXiv.org.
    11. Fernandes, Marcelo & Grammig, Joachim, 2005. "Nonparametric specification tests for conditional duration models," Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July.
    12. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    13. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram, 2013. "The empirical content of Cournot competition," Journal of Economic Theory, Elsevier, vol. 148(4), pages 1552-1581.
    14. Jehiel, Philippe & Lamy, Laurent, 2014. "On discrimination in procurement auctions," CEPR Discussion Papers 9790, C.E.P.R. Discussion Papers.
    15. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Dominic Coey & Bradley Larsen & Kane Sweeney, 2019. "The bidder exclusion effect," RAND Journal of Economics, RAND Corporation, vol. 50(1), pages 93-120, March.
    17. Gayle, Wayne-Roy & Namoro, Soiliou Daw, 2013. "Estimation of a nonlinear panel data model with semiparametric individual effects," Journal of Econometrics, Elsevier, vol. 175(1), pages 46-59.
    18. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    19. Ying Wang & Peter C. B. Phillips & Yundong Tu, 2024. "Limit Theory and Inference in Non-cointegrated Functional Coefficient Regression," Cowles Foundation Discussion Papers 2399, Cowles Foundation for Research in Economics, Yale University.
    20. Chung Choe & Alfonso Flores-Lagunes & Sang-Jun Lee, 2015. "Do dropouts with longer training exposure benefit from training programs? Korean evidence employing methods for continuous treatments," Empirical Economics, Springer, vol. 48(2), pages 849-881, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ubc:pmicro:vadim_marmer-2010-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Maureen Chin (email available below). General contact details of provider: http://www.economics.ubc.ca/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.